In this course, we aim at detailing state-of-the-art advancement of metabolomics, which represents a powerful approach and an alternative to the classical other omics. It represents a better phenotypic picture by reflecting the biochemical activity of the cells. This course will provide an overview of handling metabolomics data (from rawdata to biological knowledge) using bioinformatics tools. It will be delivered using a mixture of lectures, computer-based practical sessions and interactive discussions
Several scientific applications require computing and/or storage resources that go beyond the processing power of a single multi-core machine. High performance computing (HPC) clusters provide the necessary hardware and software infrastructure to efficiently run computing intensive applications. The course gives an introduction to high performance computing using the HPC cluster at Vital-IT. Both theoretical as well as practical usage aspects will be covered.
Usage of NGS is increasing in several biological fields due to a very rapid decrease in cost. However, it often results in hundreds of Gbs of data making the downstream analysis very challenging and requires bioinformatics skills.
In this module, we will introduce the most used sequencing technologies and explain their decryption concepts.
We will also introduce the repositories e.g. the European Nucleotide Archive (ENA), Sequence Read Archive (SRA) from which you could retrieve raw data based on specific experiments. We will practice the usage of command line tools to search and fetch NGS raw data in a powerful way.
Finally, using different datasets, we will practice screening for quality control, filtering reads for better downstream analysis, mapping reads to reference genome and visualize the output.
This course is aimed at preparing the audience for the hands-on course on protein structure visualisation.
The goal of this course is to expose the participants to 3-dimensional structures of proteins. It describes the experimental methods used to solve these structures, and databases used to archive, annotate and classify protein structures. Analysis and visualisation software will be used to display, analyze, compare and interpret protein structures. Students will also be introduced to protein structure prediction by homology modeling techniques.
The second part of the course is dedicated molecular modelling, introduction to docking of small molecules (drugs, peptides) to large macromolecules and Molecular graphics.